Public Funding for Computerised Information Technology Limited

"The first phase of the project will demonstrate the feasibility of using agile mobile wall-climbing robots, portable radiography equipment and artificial intelligence (AI) technologies to perform asset management of off-shore wind farms located in extreme and challenging environments. Gaining access to off-shore wind turbine blades is difficult and expensive e.g. with large cranes on ships or climbing with rope/platform systems. Because of the difficulty of deploying large systems off-shore, a modular approach is required to easily transport lightweight systems to test sites and assemble them quickly. A modular wall climbing robot, assembled on site, will carry the radiography deployment system up the wind tower. Two arms will extend on either side of a blade positioned in a 90 degree configuration so that the source and detector are on either side of the blade. An intelligent positioning system will keep the two aligned and normal to each other as the complex aerodynamic shape of the blade is inspected along the width of the blade. The climbing robot will then move a small distance up the tower and repeat coverage of the blade width. Allowing a full length of the blade, with inspection starting from the tip of the blade up to the blade root. An intelligent control positioning system will be required since the blade shape and curvature will be different in each horizontal plane and the source/detector will need to adapt to the shape for optimum imaging. To cope with blade in-plane and out-of-plane vibrations, the X-ray source and detector will be kept stationary with respect to a blade by designing passive compliance into the deployment arm. Embedded intelligence will carry out automated defect detection and classification and enable autonomous decision making for further inspection and intervention."

"New challenges are present for offshore oil and gas operators to provide adequate integrity assurance of their assets as the production facilities are reaching for the deep-water areas. Challenging conditions arise from more corrosive environments, higher pressures and temperatures. In deep water and hostile environments, where loading is high and complex and often design methods are pushed to the limit of current industry capability and experience, the riser systems have received an increased focus, more than ever in the light of several operational incidents (like the Deepwater Horizon accident in the Gulf of Mexico). These accidents have caused operators and regulators to question and update codes of practice. Flexible risers pipes are by nature complicated in design with many varying material types, corresponding to challenges in the inspection and integrity evaluation. The inspection techniques currently available in the market consist of only irregular diver or Remotely Operated Vehicle (ROV) inspections and are able to inspect only the near side layers for wire disruptions, with the far side layers remaining uninspected. The RobotX project will investigate the feasibility of a robotic digital x-ray scanning system that will address the needs and challenges of deep water flexible risers inspection. The robot and digital radiography equipment would have to withstand harsh environmental conditions i.e. high pressure (100bar). The system will perform a see--through quick scan as it crawls and process the data using innovative image processing methods and categorise them using machine learning. If defects are detected the robotic system will be able to turn around the riser and perform a more thorough scan. The defect will be correctly identified, using images taken at several angles. These innovations will allow not just to detect and locate the defects, but also classify them according to an existing historical database and automatically decide on bespoke scans for assessing the severity and needs for future intervention."

The use of additive manufactured (AM) components is increasing rapidly throughout key global industries. Many industrial applications for Additive Manufacturing have been developed over the last five years or so. Industries such as aerospace, automotive and medical are embracing the advantages of AM and implementing the technology successfully. AM projected value, including products and services, is valued at £5 billion in 2015 are forecasted to be £13 billion by 2021. Despite the huge potential that additive manufacturing offers, it is currently limited due to inaccuracy in manufacturing of parts,varying shape and different materials. Slow processing time and cost of post processing hinders the wider adoption of Additive Manufacturing for various industrial sectors including aviation. ADD-CAD will offer a software/Add-on solution for laser blown deposition additive manufacturing that will ultimately improve the design accuracy by 90% and will reduce the post machining and processing time and will help to prevent material waste, save up to 8% on materials costs, energy use and carbon emissions, preventing product recalls for manufacturers, facilitating market growth and generate new AM manufacturing sector jobs. ADD-CAD will be created through a powerful supply chain of 1 key AM systems and service provider SME, 2 innovative product manufacturer SMEs and 2 research organisations.

Failure of mooring chains that secure floating structures in off-shore production of oil and gas results in oil leaks due to the rupture of flexible pipes that bring product to the surface. The clean-up costs of environmental pollution run into hundreds of millions of pounds. It is therefore important to inspect the mooring chain links to assess the extent of corrosion, fatigue cracking and developing weld faults before they result in failure of a chain. It is very expensive to remove a chain weighing many tons and bring it to shore to inspect it. Savings can be made by perfoming non-destructive testing (NDT) of a chain in-situ while it is in operation. The heavy chains generate large dynamic forces so that inspection using divers is extremely hazardous. The project aims to develop a small, compact mobile robot that can climb on mooring chains both underwater and in air to scan chain links with advanced ultrasound sensors. The robotic NDT system will provide a tool to assess the condition of mooring chains to enable asset managers to make decisions on repair and remaining lifetime of a chain. It will reduce inspection costs by speeding up coverage of a mooring chain and remove the need for diver inspection which costs £40,000 per floating structure and puts their lives at risk.

Net shape parts of typically intricate and complex shape obtained by powder metallurgy (PM) are employed in several key mass industry sectors, especially automotive, aerospace and medical. Their use is growing rapidly in preference to conventional casting because the process produces parts in the precise final shape required with little or no machining requirement combined with fine grained (nano-micro scale), homogeneous microstructures of enhanced strength. However there is a lack of production quality control as little in-line inspection is performed. End-of-line inspection, not often performed, leads to scrapping of 6-8% of components yet fails to detect micro sized defects, which can grow in service to produce major in service failures and recalls. THE PROJECT VISION is an in-line quality control system (QUALINET) using 3D microfocus x ray imaging (µXCT) with AUTOMATION INNOVATIONS (A) Detection and characterization of volume and surface micro-scale defects at the pre and post sintering stages. (B) Decision making: (i) component acceptance or (ii) send for recycling or (iii) send with a prescription for defect healing treatment. QUALINET will eliminate waste, increasing line production, reducing energy consumption and carbon emissions, all by 8%. The benefit will be optimal for state of the art PM component lines including additive manufacturing by laser deposition, nano-powders and injection moulding. Estimated ROI comprising the profits of the partners, licensees and the savings in reduced waste from the PM systems on which the QUALINET sold system would be installed are 111:1 in the EEA and 35:1 over the first 5 years of commercialisation. Global acceptance of the net technolgy could save £340mpa.

The public description for this project has been requested but has not yet been received.